Paper: KnowNet: Building a Large Net of Knowledge from the Web

ACL ID C08-1021
Title KnowNet: Building a Large Net of Knowledge from the Web
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2008
Authors

This paper presents a new fully auto- matic method for building highly dense and accurate knowledge bases from ex- isting semantic resources. Basically, the method uses a wide-coverage and accu- rate knowledge-based Word Sense Dis- ambiguation algorithm to assign the most appropriate senses to large sets of topi- cally related words acquired from the web. KnowNet, the resulting knowledge-base which connects large sets of semantically- related concepts is a major step towards the autonomous acquisition of knowledge from raw corpora. In fact, KnowNet is sev- eral times larger than any available knowl- edge resource encoding relations between synsets, and the knowledge KnowNet con- tains outperform any other resource when is empirically evaluated in a common framework.